Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images

@article{Lu2020DataEA,
  title={Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images},
  author={Ming Y. Lu and Drew F. K. Williamson and Tiffany Y. Chen and Richard J. Chen and Matteo Barbieri and Faisal Mahmood},
  journal={Nature biomedical engineering},
  year={2020}
}
Deep-learning methods for computational pathology require either manual annotation of gigapixel whole-slide images (WSIs) or large datasets of WSIs with slide-level labels and typically suffer from poor domain adaptation and interpretability. Here we report an interpretable weakly supervised deep-learning method for data-efficient WSI processing and learning that only requires slide-level labels. The method, which we named clustering-constrained-attention multiple-instance learning (CLAM), uses… 
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287 Citations
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287 Citations

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